PROJECT SUMMARY Hydrocephalus, an imbalance between cerebrospinal fluid production and absorption, is diagnosed in more than 1 in 500 people in the United States. Approximately 80% of these patients will suffer long-term neurological deficits. Genetic diseases, meningitis, subarachnoid hemorrhage, stroke, traumatic brain injury, or tumors cause hydrocephalus. The common treatment for all hydrocephalus patients is CSF drainage by shunting. Despite all our efforts, shunts still have the highest failure rate of any neurological device. A shocking 98% of shunts fail after just ten years, a rate bumped up by the 80% of patients who suffer from tens if not hundreds of repetitive shunt failures. Shunts fail after becoming obstructed with attaching glia, creating a substrate for more glia or other cells and tissues (e.g. choroid plexus) to secondarily bind and block the flow of CSF through the shunt. Since glial attachment is a primary mechanism for shunt failure, we need to find out what it is about the pathophysiology of hydrocephalus that cause glia to attach and cause repetitive shunt failure. Until these cues are identified, we cannot address shunt failure in a principled way. In this supplement, we focus specifically on how flow and pressure influence glia to attach. We do this using the same general approaches to the parent R01: in our first approach, we correlate patient data to changes in cell attachment, hypothesizing that it is non-physiologic ICP flux that shifts glial cell attachment. In our second approach, we probe the mechanisms of shunt failure due to ever-present glia, specifically, how glial attachment changes as a function of flow and pressure by controlling these factors in our 3D cell culture system. Methods include a first application of high-throughput, high-resolution, multi-spectral imaging and use of Arduino-based technologies to record, then subsequently control flow and pressure independently. These data can be used in future projects to predict how pathophysiologic levels of flow and pressure influence individualized patient treatment.